1. Field of the Invention
This invention relates to spread spectrum signal demodulator and, more particularly, to spread spectrum signal demodulator used for cellular communication systems, indoor wireless communication systems, wireless LAN (local area network) systems, etc.
2. Description of the Prior Art
In systems dealing with spread spectrum signals for code division multiple access (CDMA), a plurality of signals are transmitted in the same band. As is well known in the art, in such a system inter-signal interference is generated in dependence on the correlation among codes assigned to individual signals. The characteristics of the signals are deteriorated more and more with increasing number of signals involved. Further, when there are signal level fluctuations, interference received by low level signals from high level signals is relatively great. In this case, the characteristics of the low level signals are greatly deteriorated.
There are some proposed methods for improving signal characteristics by reducing such inter-signal interference. One such method is called a replica signal cancellation method. In this method, replica signals produced from original signals are subtracted from the original signals to reduce the interference. This can be realized with a system as shown in FIG. 1. In the illustrated system, the number K of signals involved is 3. The system comprises correlators 11 to 13, re-modulators 501 to 503, adders 511 to 513, a delay unit 52, subtractors 531 to 533, and correlators 541 to 543.
As a spectrum spreading system, a direct spreading system is assumed. A received signal r(t) at instant t is expressed by formula 1 in FIG. 2. Here, baseband signal processing is assumed, and all the signals are assumed to be represented by complex signals.
In the formula 1, K represents the number of simultaneously transmitted signals, a.sub.k the reception amplitude level of the k-th signal, b.sub.k (i) the information bit of the i-th symbol of the k-th signal, c.sub.k (.tau.)(.vertline.c.sub.k (.tau.).vertline.)=1, 0.ltoreq..tau.&lt;T, T: symbol cycle) the spreading code of the k-th signal, .tau..sub.k the delay of the k-th signal, and n(t) the noise added on the transmission line.
With the received signal r(t), the correlators 11 to 13 each perform a process as expressed by formula 2 in FIG. 2 on each signal symbol to output a correlation y.sub.k (i). Complex conjugate is represented by *. The re-modulators 501 to 503 each re-modulate each correlation as expressed by formula 3 in FIG. 2 to generate a replica signal u.sub.k (t).
Then, when cancelling interference by the other signals than the n-th signal, the adders 511 to 513 derive the sum v.sub.n (t) of the replica signals of the other signals than the n-th signal through an operation as expressed by formula 4 in FIG. 2.
Subsequently, the subtractors 531 to 533 derive a signal w.sub.n (t) as a result of cancellation of the other signals than the n-th signal by subtracting the signal v.sub.n (t) from a delayed received signal r(t-D) as expressed by formula 5 in FIG. 2.
Then, with respect to the signal w.sub.n (t) the correlators 541 to 543 derive a correlation z.sub.n (i) as expressed by formula 6 in FIG. 2 for each symbol, thus attaining correlation detection of the interference-cancelled signal.
The processes as represented by the above formulas 4 and 5 are performed with respect to each of the 1-st to K-th signals, whereby the interference cancellation and the correlation detection are attained with respect to all the signals. The correlation detection outputs with respect to the individual signals that are obtained in the above way are phase synchronized or processed likewise and bit judged. In this way, the individual signals can be demodulated.
Another proposed method of improving the characteristics of signals through inter-signal interference cancellation is called a decorrelating method. In this method, decorrelation is performed by using known intercode correlation. The method can be carried out by a system as shown in FIG. 3, comprising correlators 11, 12, . . . , 1K and a decorrelator 61.
As in the previous case, it is assumed that the received signal is expressed by the formula 1. Further, for the brevity of the description it is assumed that there is inter-signal symbol timing synchronization and that the condition expressed by formula 7 in FIG. 2 is satisfied. In this method, the received signal r(t) is sampled at a sufficiently short interval .DELTA.T, and each symbol sample is represented by a vector of formula 8 in FIG. 2. In the formula 8, ( ).sup.T represents transposition.
Further, the product of the reception amplitude level and bit information of signal is represented by a vector of formula 9 in FIG. 2. Likewise, the spreading code c.sub.k (.tau.) of each signal is sampled at an interval .DELTA.T and represented by a vector of formula 10 in FIG. 2. Further, with all the spreading code vectors a spreading code matrix C is defined as given by formula 11 in FIG. 2. Further, the noise n(t) is sampled at an interval .DELTA.T, and the sample for each symbol is represented by a vector of formula 12 in FIG. 2. Using the above expressions, the formula 1 can be modified to formula 13 in FIG. 4.
Further, the process of the above formula 2 performed by the correlators 11 to 1K can be expressed by formula 14 in FIG. 4. Here, the outputs of the correlators 11 to 1K are represented by vectors defined by formula 15 in FIG. 4. By so doing, the formula 14 can be written as formula 16 in FIG. 4. By substituting the formula 13 into the formula 16, formula 17 in FIG. 4 can be obtained. Here, H is defined by formula 18 in FIG. 4 as a correlation matrix representing inter-code correlations.
The decorrelator 61 performs a process after formula 19 in FIG. 4 on the correlator outputs. Here, vector d(i) is represented by formula 20 in FIG. 4. Each element d.sub.k (i) is the result of decorrelation from the individual correlator outputs. Since the code matrix C is known, the correlation matrix H can be calculated in advance, and also the inverse matrix H.sup.-1 can be obtained in advance. The signal obtained by the above decorrelation is expressed by formula 21 in FIG. 4 by substituting the formula 17 into the formula 19.
For the sake of the brevity, d(i) may be expressed by a formula for each vector element, that is, by formula 22 in FIG. 4. This means that the decorrelated signal d.sub.k (i) is the sum of the product of the amplitude level a.sub.k and information bit b.sub.k (l) of the original signal and a noise component n'.sub.k (i), and is not influenced by the simultaneously received other signals at all. This means cancellation of the inter-signal interference, that is, interferencecancelled detection signals are obtainable. Each interference-cancelled detection signal is phase synchronized or likewise processed and bit judged. In this way, each signal can be demodulated.
While the decorrelating method has been described in connection with its operation when there is symbol synchronization, in the case of absence of synchronization, like the case of presence of synchronization the decorrelation is obtainable as shown in "Near-far Resistance of Multiuser Detectors in Asynchronous Channels" (R. Lupas, S. Verdu, IEEE Trans. Com. Vol. 38, No. 4, April 1990). More specifically, regarding a period MT which is sufficiently long with respect to K asynchronous signals and covers a plurality of (i.e., M) symbols to be a period of one synchronous symbol, it can be considered that MK synchronous signals are transmitted in the period MT. Thus, it is possible to obtain decorrelation in the asynchronous signal case through decorrelation in the case of the MK signals.
In the prior art replica signal cancellation method, influence of interference signals appears in the correlator output obtainable according to the formula 2 due to inter-code correlation. Therefore, the replica signal generated according to the formula 3 contains an error due to the interference. More specifically, the interference-cancelled signal Z.sub.n (i) obtained according to the formula 5 is not perfectly free from interference, and therefore its characteristics are deteriorated compared to the case in which interference is perfectly cancelled. Particularly, in cases when a large number of signals are involved and when the level differences among signals are large, the residual interference are greatly influential, thus resulting in great deterioration of the signal characteristics.
Further, in the prior art replica signal cancellation method, the process of the formula 4 has to be performed for each signal. This means that in the case of digital process arithmetic operation has to be performed a number of times substantially equal to the square of the number K of the involved signals for each sample together with the process of the formula 5. Therefore, if the number of signals is large, it dictates an enormous process amount.
The prior art decorrelating method permits obtaining perfectly interference-cancelled detection signal. However, the method poses the following problem. When the number of signals is changed, the size of the correlation matrix H is changed. In this case, it is necessary to calculate afresh the inverse matrix H.sup.-1 which is used for the decorrelation. Further, when spreading codes are altered or changed, the spreading code matrix C defined by the formula 11 is changed, thus changing the correlation matrix H defined by the formula 18. Therefore, again it becomes necessary to calculate the inverse matrix H.sup.-1 afresh. In the case of absence of symbol synchronization, a change in the signal delay similarly changes the correlation of the spreading codes to one another, thus changing the correlation matrix defined for the asynchronous signal case. Therefore, again in this case it becomes necessary to calculate the inverse matrix used for the decorrelation afresh.
The size of the matrix H is K.times.K in the case of presence of the symbol synchronization and MK.times.MK in the asynchronous case. As an example, where the number K of signals is 100, an inverse matrix to a matrix with a size of 100.times.100 has to be calculated even if there is symbol synchronization. In the case of absence of symbol synchronization, using a correlation matrix of (M=) 10 symbols, for instance, it is necessary to calculate an inverse matrix to a matrix of 1,000.times.1,000 in size. This means an enormous operation amount. In cases where signals are frequently turned on and off due to voice activation or the like or in cases of mobile communication where there are quick changes in delay, it is difficult to calculate the above inverse matrix by real time calculation, thus making it impossible to adopt the decorrelating receiver.
Further, using spreading code which has a greater length than the symbol length, is equivalent to using different codes for the individual symbols. In this case, the correlation matrix H varies with the symbol, that is, it is necessary to adopt different inverse matrices H.sup.-1 for the individual symbols. Therefore, the problem of operation amount increase is posed again.